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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# CliMA Vegetation model\n",
    "---\n",
    "Modules:\n",
    "\n",
    "Compute leaf optical properties for standard values\n",
    "\n",
    "Compute canopy radiation (both reflectance as well as within canopy distributions for SW energy balance)\n",
    "\n",
    "Compute photosynthesis\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Add PATH (adapt!)\n",
    "push!(LOAD_PATH, \"/Users/braghier/Documents/CliMA/CliMA-land_copy/Land/src/Leaf/\");\n",
    "push!(LOAD_PATH, \"/Users/braghier/Documents/CliMA/CliMA-land_copy/Land/src/Utils/\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Canopy optical module\n",
    "---\n",
    "Fixed leaf optical properties within canopt (can be changed to vertical explicity approach later as in mSCOPE)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "┌ Info: Precompiling PhysCon [top-level]\n",
      "└ @ Base loading.jl:1273\n",
      "┌ Info: Precompiling WaterVaporMod [top-level]\n",
      "└ @ Base loading.jl:1273\n",
      "┌ Info: Precompiling MathTools [top-level]\n",
      "└ @ Base loading.jl:1273\n",
      "┌ Warning: Module MathTools with build ID 99790507312435 is missing from the cache.\n",
      "│ This may mean MathTools [top-level] does not support precompilation but is imported by a module that does.\n",
      "└ @ Base loading.jl:1011\n",
      "┌ Info: Precompiling CanopyRTMod [top-level]\n",
      "└ @ Base loading.jl:1273\n",
      "┌ Warning: Module Leaf with build ID 99791047511914 is missing from the cache.\n",
      "│ This may mean Leaf [top-level] does not support precompilation but is imported by a module that does.\n",
      "└ @ Base loading.jl:1011\n",
      "┌ Info: Skipping precompilation since __precompile__(false). Importing CanopyRTMod [top-level].\n",
      "└ @ Base loading.jl:1028\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Reading Optical Parameters from 400.0 to 2380.0 length: 115\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "┌ Warning: Use of `Poly` from v1.0 forward will require `using Polynomials.PolyCompat`\n",
      "│   caller = Polynomials.PolyCompat.Poly(::Array{Float32,1}) at Poly.jl:26\n",
      "└ @ Polynomials.PolyCompat /Users/braghier/.julia/packages/Polynomials/ghqdF/src/polynomials/Poly.jl:26\n",
      "┌ Info: Precompiling BenchmarkTools [6e4b80f9-dd63-53aa-95a3-0cdb28fa8baf]\n",
      "└ @ Base loading.jl:1273\n",
      "┌ Info: Precompiling Plots [91a5bcdd-55d7-5caf-9e0b-520d859cae80]\n",
      "└ @ Base loading.jl:1273\n"
     ]
    }
   ],
   "source": [
    "#Loading required modules\n",
    "using PhysCon\n",
    "using WaterVaporMod\n",
    "using MathTools\n",
    "using Leaf\n",
    "using CanopyRTMod\n",
    "using BenchmarkTools\n",
    "using Statistics\n",
    "using Plots"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Run Fluspect\n",
    "\n",
    "Leaf optical property generator (provides reflectance and transmittance)\n",
    "\n",
    "---\n",
    "\n",
    "INPUT: \n",
    "\n",
    "1) optis = optipar{typ}(loadOpti(swl)...);\n",
    "\n",
    "A list of input variables related to leaf biological status is defined in PhotoStructs.jl, including:     \n",
    "\n",
    "    \"Leaf structure parameter\"\n",
    "    N::FT    = 1.5       # | -          | (1.0, 3.0)  | \"Leaf structure parameter\"\n",
    "    \"Chlorophyll a+b content\"\n",
    "    Cab::FT  = 40.0      # | μg cm^-2   | (0.0, 110)  | \"Chlorophyll a+b content\"\n",
    "    \"Carotenoid content\"\n",
    "    Car::FT  = 10.0      # | μg cm^-2   | (0.0, 40.0) | \"Carotenoid content\"\n",
    "    \"Anthocynanin content\"\n",
    "    Ant::FT  = 8.0       # | μg cm^-2   | (0.0, 40.0) | \"Anthocynanin content\"\n",
    "    \"Senescent material fraction\"\n",
    "    Cs::FT   = 0.0       # | -          | (0.0, 1.0)  | \"Senescent material fraction\"\n",
    "    \"Equivalent water thickness\"\n",
    "    Cw::FT   = 0.015     # | cm         | (0.0, 0.05) | \"Equivalent water thickness\"\n",
    "    \"Dry matter content (dry leaf mass per unit area)\"\n",
    "    Cm::FT   = 0.01      # | g cm^-2    | (0.0, 0.2)  | \"Dry matter content (dry leaf mass per unit area)\"\n",
    "    \"Fractionation between Zeaxanthin and Violaxanthin in Car (1=all Zeaxanthin)\"\n",
    "    Cx::FT   = 0.0       # | -          | (0.0, 1.0)  | \"Fractionation between Zeaxanthin and Violaxanthin in Car (1=all Zeaxanthin)\"\n",
    "    \"Broadband thermal reflectance\"\n",
    "    ρ_LW::FT = 0.01      # | -          | (0.0, 1.0)  | \"Broadband thermal reflectance\"\n",
    "    \"Broadband thermal transmission\"\n",
    "    τ_LW::FT = 0.01      # | -          | (0.0, 1.0)  | \"Broadband thermal transmission\"\n",
    "    \"Leaf fluorescence efficiency\"\n",
    "    fqe::FT = 0.01       # | -          | (0.0, 1.0)  | \"Leaf fluorescence efficiency\"\n",
    "    \n",
    "OUTPUT:\n",
    "\n",
    "2) leaf   = leafbio{typ}(ρ_SW=similar(wl),τ_SW=similar(wl), kChlrel=similar(wl), Mb=zeros(typ,length(wle), length(wlf)), Mf=zeros(typ,length(wle), length(wlf)) );\n",
    "\n",
    "    \" leaf reflectance\"\n",
    "    ρ_SW::Array{FT,1}    # | -          | (0.0, 1.0)  | \" leaf reflectance\"\n",
    "    \n",
    "    \" leaf transmittance\"\n",
    "    τ_SW::Array{FT,1}    # | -          | (0.0, 1.0)  | \" leaf transmittance\"\n",
    "    \n",
    "    \"relative absorption by Chlorophyll\"\n",
    "    kChlrel::Array{FT,1} # | -          | (0.0, 1.0)  | \"relative absorption by Chlorophyll\"\n",
    "    \n",
    "    \"Fluorescence excitation matrix backwards\"\n",
    "    Mb::Array{FT,2}      # | -          | (0.0, 1.0)  | \"Fluorescence excitation matrix backwards\"\n",
    "    \n",
    "    \"Fluorescence excitation matrix forwards\"\n",
    "    Mf::Array{FT,2}      # | -          | (0.0, 1.0)  | \"Fluorescence excitation matrix forwards\"\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "106.310779 seconds (135.84 M allocations: 5.026 GiB, 2.27% gc time)\n",
      "  0.000768 seconds (3.10 k allocations: 996.719 KiB)\n",
      "  0.000657 seconds (3.10 k allocations: 996.719 KiB)\n",
      "  0.000631 seconds (3.10 k allocations: 996.719 KiB)\n",
      "  0.000626 seconds (3.10 k allocations: 996.719 KiB)\n",
      "  0.000652 seconds (3.10 k allocations: 996.719 KiB)\n",
      "  0.000681 seconds (3.10 k allocations: 996.719 KiB)\n",
      "  0.000688 seconds (3.10 k allocations: 996.719 KiB)\n",
      "  0.000685 seconds (3.10 k allocations: 996.719 KiB)\n",
      "  0.001050 seconds (3.10 k allocations: 996.719 KiB)\n",
      "  0.001011 seconds (3.10 k allocations: 996.719 KiB)\n",
      "  0.000710 seconds (3.10 k allocations: 996.719 KiB)\n",
      "  0.000676 seconds (3.10 k allocations: 996.719 KiB)\n",
      "  0.000709 seconds (3.10 k allocations: 996.719 KiB)\n",
      "  0.000690 seconds (3.10 k allocations: 996.719 KiB)\n",
      "  0.000682 seconds (3.10 k allocations: 996.719 KiB)\n",
      "  0.000694 seconds (3.10 k allocations: 996.719 KiB)\n",
      "  0.000692 seconds (3.10 k allocations: 996.719 KiB)\n",
      "  0.000673 seconds (3.10 k allocations: 996.719 KiB)\n",
      "  0.000668 seconds (3.10 k allocations: 996.719 KiB)\n",
      "  0.000725 seconds (3.10 k allocations: 996.922 KiB)\n",
      "  6.731252 seconds (21.03 M allocations: 844.287 MiB, 3.56% gc time)\n",
      "  7.556549 seconds (70.83 M allocations: 2.384 GiB, 11.29% gc time)\n"
     ]
    }
   ],
   "source": [
    "wl = CanopyRTMod.wl;\n",
    "wle = CanopyRTMod.wle;\n",
    "wlf = CanopyRTMod.wlf;\n",
    "\n",
    "arrayOfLeaves = Array{leafbio{FT,length(wl), length(wle), length(wlf),length(wle)*length(wlf)}, 1}(undef, CanopyRTMod.canopy.nlayers)\n",
    "for i = 1:CanopyRTMod.canopy.nlayers\n",
    "    #@show i\n",
    "    arrayOfLeaves[i] = leafbio{FT, length(wl), length(wle), length(wlf),length(wle)*length(wlf)}()\n",
    "    @time CanopyRTMod.fluspect!(arrayOfLeaves[i], CanopyRTMod.optis)\n",
    "end\n",
    "\n",
    "#How long does Fluspect take to run per layer? \n",
    "@time CanopyRTMod.fluspect!(leaf, CanopyRTMod.optis)\n",
    "@time CanopyRTMod.computeCanopyGeomProps!(canopy, angles,canOpt)\n",
    "@time CanopyRTMod.computeCanopyMatrices!(arrayOfLeaves,canOpt);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# What are the spectral values of reflectance and transmittance?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
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      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot(CanopyRTMod.optis.lambda, leaf.ρ_SW, label=\"Reflectance\")\n",
    "plot!(CanopyRTMod.optis.lambda, 1 .-leaf.τ_SW, label=\"1-Transmittance\")\n",
    "xlabel!(\"lambda (nm)\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Canopy Radiative Transfer module  \n",
    "\n",
    "An adapted version of PRO-SAIL with PROSPECT-D but also adding within canopy radiation via SCOPE\n",
    "\n",
    "---\n",
    "\n",
    "INPUT:\n",
    "\n",
    "FluspectMod.leaf -> Leaf optical properties (see Fluspect variables)\n",
    "\n",
    "FluspectMod.canopy -> Canopy structural properties\n",
    "\n",
    "    \"number of canopy layers\"\n",
    "    nlayers::Int64     = 20    # | -          | (2, 60)      | \"number of canopy layers\"\n",
    "    \"Leaf Area Index\"\n",
    "    LAI::FT            = 3.0   # | -          | (0.0, 9.0)   | \"Leaf Area Index\"\n",
    "    \"Clumping factor\"\n",
    "    Ω::FT             = 1.0   # | -          | (0.0, 1.0)   | \"clumping factor\"\n",
    "    \"Leaf width\"\n",
    "    leafwidth::FT      = 0.1   # | m          | (0.0, 1.0)   | \"Leaf width\"\n",
    "    \"Vegetation height\"\n",
    "    hc::FT             = 2.0   # | m          | (0.0, 70.0)  | \"Vegetation height\"\n",
    "    \"Leaf Inclination\"\n",
    "    LIDFa::FT          = -0.35 # | -          | (-1.0, 1.0)  | \"Leaf Inclination\"\n",
    "    \"Variation in leaf inclination\"\n",
    "    LIDFb::FT          = -0.15 # | -          | (-1.0, 1.0)  | \"Variation in leaf inclination\"\n",
    "    \"HotSpot parameter (still need to check!)\"\n",
    "    hot::FT            = 0.05  # | -          | (0, 1.0)     | \"HotSpot parameter (still need to check!)\"\n",
    "    \"Leaf distribution type (2=campbell, 1=ladgen)\"\n",
    "    TypeLidf::FT       = 1     # | -          | (-1.0, 1.0)  | \"Leaf distribution type (2=campbell, 1=ladgen)\"\n",
    "    \"leaf azimuth angles relative to the sun\"\n",
    "    lazitab::Array{FT} = collect(5.0:10.0:355.0)\n",
    "    \n",
    "FluspectMod.angle -> Sun/Observation angular properties\n",
    "\n",
    "    \"Solar Zenith Angle in degrees\"\n",
    "    tts::FT=45\n",
    "    \"Viewing Zenith Angle in degrees\"\n",
    "    tto::FT=0\n",
    "    \"relative azimuth in degrees\"\n",
    "    psi::FT=0\n",
    "    \n",
    "FluspectMod.sunRad -> Incoming Shortwave Radiation (read from test case now, but coming from the atmosphere later on)\n",
    "\n",
    "    \"Spectral direct radiation at top of canopy\"\n",
    "    Edir =  suni[\"Edirect\"]\n",
    "    \"Spectral direct radiation at top of canopy\"\n",
    "    Ediff =  suni[\"Ediffuse\"]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### How does the Incoming Shortwave Radiation spectral curve look like?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
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      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot(CanopyRTMod.wl,CanopyRTMod.sunRad.E_diffuse, label=\"Diffuse incoming top of canopy\")\n",
    "plot!(CanopyRTMod.wl,CanopyRTMod.sunRad.E_direct, label=\"Direct incoming top of canopy\")\n",
    "ylabel!(\"mW m-2 μm-1\")\n",
    "xlabel!(\"lambda (nm)\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "OUTPUT:\n",
    "\n",
    "    \"integrated TOC outgoing flux\"\n",
    "    intEout::FT                       # | W m^-2               | (0.0, 2500)  | \"integrated TOC outgoing flux\"\n",
    "    \"incident spectrally integrated total PAR\"\n",
    "    PAR::FT                           # | moles m^-2 s^-1      | (0.0, 2.5e-9)| \"incident spectrally integrated total PAR\"\n",
    "    \"incident spectrally integrated direct PAR\"\n",
    "    PAR_direct::FT                    # | moles m^-2 s^-1      | (0.0, 2.5e-9)| \"incident spectrally integrated direct PAR\"\n",
    "    \"incident spectrally integrated diffuse PAR\"\n",
    "    PAR_diffuse::FT                   # | moles m^-2 s^-1      | (0.0, 2.5e-9)| \"incident spectrally integrated diffuse PAR\"\n",
    "    \"net radiation of shaded soil\"\n",
    "    Rnhs::FT                          # | W m^-2               | (0.0, 2500)  | \"net radiation of shaded soil\"\n",
    "    \"net radiation of sunlit soil\"\n",
    "    Rnus::FT                          # | W m^-2               | (0.0, 2500)  | \"net radiation of sunlit soil\"\n",
    "    \"extinction cofficient in the solar direction\"\n",
    "    k::FT\n",
    "    \"extinction cofficient in the viewing direction\"\n",
    "    K::FT\n",
    "\n",
    "    # Dim of nLayers+1\n",
    "    \"gap fraction in the solar direction\"\n",
    "    Ps::Array{FT,1}\n",
    "    \"gap fraction in the viewing direction\"\n",
    "    Po::Array{FT,1}\n",
    "    \"bi-derectional gap fraction (solar->canopy->viewing)\"\n",
    "    Pso::Array{FT,1}\n",
    "\n",
    "    # Dim of nLayers\n",
    "    \"net radiation of shaded leaves\"\n",
    "    Rnhc::Array{FT,1}                 # | W m^-2               | (0.0, 2500)  | \"net radiation of shaded leaves\"\n",
    "    \"net PAR of shaded leaves\"\n",
    "    Pnh::Array{FT,1}                  # | moles m^-2 s^-1      | (0.0, 2.5e-9)| \"net PAR of shaded leaves\"\n",
    "    \"net PAR absorbed by Cab of shaded leaves\"\n",
    "    Pnh_Cab::Array{FT,1}              # | moles m^-2 s^-1      | (0.0, 2.5e-9)| \"net PAR absorbed by Cab of shaded leaves\"\n",
    "    \"net PAR absorbed by shaded leaves\"\n",
    "    Rnh_PAR::Array{FT,1}              # | W m^-2               | (0.0, 2500)  | \"net PAR absorbed by shaded leaves\n",
    "\n",
    "    # Dimension of wavelength only:\n",
    "    \"TOC outgoing radiance in observation direction\"\n",
    "    Lo::Array{FT,1}                   # | mW m^-2 μm^-1 sr^-1  | (0.0, 2500)  | \"TOC outgoing radiance in observation direction\"\n",
    "    \"TOC outgoing radiation\"\n",
    "    Eout::Array{FT,1}                 # | mW m^-2 μm^-1        | (0.0, 2500)  | \"TOC outgoing radiation\"\n",
    "    \"incident direct radiation at top of canopy\"\n",
    "    inc_SW_direct::Array{FT,1}        # | mW m^-2 μm^-1        | (0.0, 2500)  | \"incident direct radiation at top of canopy\"\n",
    "    \"incident diffuse radiation at top of canopy\"\n",
    "    inc_SW_diffuse::Array{FT,1}       # | mW m^-2 μm^-1        | (0.0, 2500)  | \"incident diffuse radiation at top of canopy\"\n",
    "    \"Albedo for direct incoming radiation\"\n",
    "    alb_direct::Array{FT,1}           # | -                    | (0.0, 1.0)   | \"Albedo for direct incoming radiation\"\n",
    "    \"Albedo for diffuse incoming radiation\"\n",
    "    alb_diffuse::Array{FT,1}          # | -                    | (0.0, 1.0)   | \"Albedo for diffuse incoming radiation\"\n",
    "\n",
    "\n",
    "    # Dimension of nLayer+1 * nWavelengths\n",
    "    \"upwelling diffuse radiation within canopy\"\n",
    "    E_up::Array{FT,2}                 # | mW m^-2 μm^-1        | (0.0, 2500)  | \"upwelling diffuse radiation within canopy\"\n",
    "    \"downwelling diffuse radiation within canopy\"\n",
    "    E_down::Array{FT,2}               # | mW m^-2 μm^-1        | (0.0, 2500)  | \"downwelling diffuse radiation within canopy\"\n",
    "\n",
    "    # Dimension of nLeafInclination * nLeafAzimuth * nLayer\n",
    "    \"net radiation of sunlit leaves\"\n",
    "    Rnuc::Array{FT,3}                 # | W m^-2               | (0.0, 2500)  | \"net radiation of sunlit leaves\"\n",
    "    \"net PAR of sunlit leaves\"\n",
    "    Pnu::Array{FT,3}                  # | moles m^-2 s^-1      | (0.0, 2.5e-9)| \"net PAR of sunlit leaves\"\n",
    "    \"net PAR absorbed by Cab of sunlit leaves\"\n",
    "    Pnu_Cab::Array{FT,3}              # | moles m^-2 s^-1      | (0.0, 2.5e-9)| \"net PAR absorbed by Cab of sunlit leaves\"\n",
    "    \"net PAR absorbed by sunlit leaves\"\n",
    "    Rnu_PAR::Array{FT,3}              # | W m^-2               | (0.0, 2500)  | \"net PAR absorbed by sunlit leaves\"\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 77.029668 seconds (89.60 M allocations: 3.112 GiB, 2.29% gc time)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "114-element StaticArrays.MArray{Tuple{114},Float32,1,114} with indices SOneTo(114):\n",
       " 0.016298749\n",
       " 0.016061665\n",
       " 0.015881296\n",
       " 0.015751388\n",
       " 0.015681438\n",
       " 0.015838094\n",
       " 0.016197663\n",
       " 0.016449228\n",
       " 0.016857475\n",
       " 0.018737108\n",
       " 0.024835993\n",
       " 0.04085269 \n",
       " 0.06982264 \n",
       " ⋮          \n",
       " 0.09234707 \n",
       " 0.100015655\n",
       " 0.10604642 \n",
       " 0.11084376 \n",
       " 0.11775029 \n",
       " 0.12267599 \n",
       " 0.11349179 \n",
       " 0.09381508 \n",
       " 0.08082256 \n",
       " 0.07373846 \n",
       " 0.067999184\n",
       " 0.063178934"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#How long does RTM_sail take to run? \n",
    "#can::struct_canopy, cO::struct_canopyOptProps, cR::struct_canopyRadiation, sun::incomingRadiation, so::struct_soil\n",
    "@time CanopyRTMod.RTM_SW!(canopy, canOpt, canRad,sunRad, CanopyRTMod.soil)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### How does canopy albedo look like?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
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      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot(CanopyRTMod.wl,CanopyRTMod.canRad.alb_direct, label=\"Albedo for direct light\")\n",
    "plot!(CanopyRTMod.wl,CanopyRTMod.canRad.alb_diffuse, label=\"Albedo for diffuse light\")\n",
    "xlabel!(\"lambda (nm)\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### What is the value of transmitted radiation reaching the soil?\n",
    "\n",
    "Soil is still defined as polynomial (depends on state vector size), still TBD in the structure mode. Currently:\n",
    "\n",
    "    pSoil =  Polynomials.Poly(typ(0.2))\n",
    "    rsoil = Polynomials.polyval(pSoil,wl.-mean(wl));\n",
    "    soil_emissivity = 1 .-rsoil # emissivity of soil (goes into structure later)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  0.000177 seconds (590 allocations: 268.906 KiB)\n",
      "Net radiation diffuse soil  12.201622\n",
      "Net radiation direct soil  0.42350906\n",
      "Net radiation soil  12.625131\n"
     ]
    }
   ],
   "source": [
    "@time CanopyRTMod.deriveCanopyFluxes!(canopy, canOpt, canRad,sunRad, CanopyRTMod.soil, arrayOfLeaves);\n",
    "\n",
    "println(\"Net radiation diffuse soil  \", CanopyRTMod.canRad.RnSoil_diffuse)\n",
    "println(\"Net radiation direct soil  \", CanopyRTMod.canRad.RnSoil_direct)\n",
    "println(\"Net radiation soil  \", CanopyRTMod.canRad.RnSoil_direct+CanopyRTMod.canRad.RnSoil_diffuse)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Leaf photosynthesis module"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a leaf structure\n",
    "l = leaf_params{Float32}();\n",
    "l2 = leaf_params{Float32}();\n",
    "# Create a Flux structure\n",
    "f = Leaf.fluxes{Float32}();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sunlit absorbed PAR  77.64748711845705\n",
      "Shaded absorbed PAR  11.176980936149524\n",
      "Total absorbed PAR  88.82447\n"
     ]
    }
   ],
   "source": [
    "# initialize some reasonable values\n",
    "f.je = 100;\n",
    "f.gbc = 100;\n",
    "f.gbv = 100;\n",
    "f.ceair =1500;\n",
    "f.eair = 1500;\n",
    "#f.APAR = 500;\n",
    "#vertical mean of net PAR absorbed by Cab of sunlit leaves\"\n",
    "APAR_sunlit = mean(CanopyRTMod.canOpt.Ps[1:end-1].*mean(CanopyRTMod.canRad.absPAR_sun*1e6, dims=1:2)[1,1,:]);  \n",
    "#vertical mean of net PAR absorbed by Cab of shaded leaves\"\n",
    "APAR_shaded = mean((1 .- CanopyRTMod.canOpt.Ps[1:end-1]).*mean(CanopyRTMod.canRad.absPAR_shade*1e6, dims=1:2)[1,1,:]);  \n",
    "f.APAR = APAR_sunlit + APAR_shaded\n",
    "println(\"Sunlit absorbed PAR  \",APAR_sunlit)\n",
    "println(\"Shaded absorbed PAR  \",APAR_shaded)\n",
    "println(\"Total absorbed PAR  \",f.APAR)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  0.000055 seconds (244 allocations: 4.953 KiB)\n"
     ]
    }
   ],
   "source": [
    "l.Kn = 2.44\n",
    "\n",
    "#Temperature em Celsius\n",
    "Temp = 24.85\n",
    "\n",
    "#How long does the leaf photosynthesis module take to run? \n",
    "@time Leaf.LeafPhotosynthesis(f,l,(Temp + 273.15),f.APAR);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Get some PAR response curves"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "20-element Array{Float32,1}:\n",
       " 10.252056  \n",
       "  7.7322383 \n",
       "  5.8914466 \n",
       "  4.190856  \n",
       "  2.8156009 \n",
       "  1.9760606 \n",
       "  1.5102638 \n",
       "  1.2587287 \n",
       "  1.1252105 \n",
       "  1.0557498 \n",
       "  1.0206299 \n",
       "  1.0036939 \n",
       "  0.9962082 \n",
       "  0.9934672 \n",
       "  0.99300694\n",
       "  0.9935877 \n",
       "  0.9945495 \n",
       "  0.99556506\n",
       "  0.99648917\n",
       "  0.99727076"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "apar = Float32[]\n",
    "gpp_sunlit_1  = Float32[]\n",
    "gpp_shaded_1  = Float32[]\n",
    "apar_ = Float32[]\n",
    "gpp_sunlit_2  = Float32[]\n",
    "gpp_shaded_2  = Float32[]\n",
    "gpp_total_1  = Float32[]\n",
    "gpp_total_2  = Float32[]\n",
    "f.cair = 400\n",
    "l.vcmax25 = 90\n",
    "l.jmax25 = 90*1.9\n",
    "l2.vcmax25 = 50\n",
    "l2.jmax25 = 50*1.9\n",
    "\n",
    "\n",
    "vertical_APAR_sunlit = CanopyRTMod.canOpt.Ps[1:end-1].*mean(CanopyRTMod.canRad.absPAR_sun*1e6, dims=1:2)[1,1,:]\n",
    "\n",
    "vertical_APAR_shaded =(1 .- CanopyRTMod.canOpt.Ps[1:end-1]).*mean(CanopyRTMod.canRad.absPAR_shade*1e6, dims=1:2)[1,1,:] \n",
    "\n",
    "vertical_APAR = vertical_APAR_sunlit .+ vertical_APAR_shaded\n",
    "\n",
    "#Sunlit\n",
    "#for f.APAR in 0:10:1000\n",
    "for f.APAR in vertical_APAR_sunlit\n",
    "    Leaf.LeafPhotosynthesis(f,l,(Temp + 273.15),f.APAR);\n",
    "    push!(apar, f.APAR)\n",
    "    push!(gpp_sunlit_1, f.an)\n",
    "    Leaf.LeafPhotosynthesis(f,l2,(Temp + 273.15),f.APAR);\n",
    "    push!(apar_, f.APAR)\n",
    "    push!(gpp_sunlit_2, f.an)\n",
    "    #println(f.APAR, \" \", f.ag, \" \", f.an)\n",
    "end\n",
    "\n",
    "#Shaded\n",
    "for f.APAR in vertical_APAR_shaded\n",
    "    Leaf.LeafPhotosynthesis(f,l,(Temp + 273.15),f.APAR);\n",
    "    push!(apar, f.APAR)\n",
    "    push!(gpp_shaded_1, f.an)\n",
    "    Leaf.LeafPhotosynthesis(f,l2,(Temp + 273.15),f.APAR);\n",
    "    push!(apar_, f.APAR)\n",
    "    push!(gpp_shaded_2, f.an)\n",
    "    #println(f.APAR, \" \", f.ag, \" \", f.an)\n",
    "end\n",
    "\n",
    "gpp_total_1 = ( CanopyRTMod.canOpt.Ps[1:end-1]).*(gpp_sunlit_1) + (1 .-CanopyRTMod.canOpt.Ps[1:end-1].*(gpp_shaded_1))\n",
    "gpp_total_2 = ( CanopyRTMod.canOpt.Ps[1:end-1]).*(gpp_sunlit_2) + (1 .-CanopyRTMod.canOpt.Ps[1:end-1].*(gpp_shaded_2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
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      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Test the impact of Vcmax on vertical photosynthesis\n",
    "plot(reverse(gpp_sunlit_1),[1:1:CanopyRTMod.canopy.nlayers],lw=3, label=\"Vcmax25=90 - sunlit\", ylabel=\"Canopy layer\", xlabel=\"An\")\n",
    "plot!(reverse(gpp_sunlit_2),[1:1:CanopyRTMod.canopy.nlayers],lw=3, label=\"Vcmax25=50 - sunlit\")\n",
    "plot!(reverse(gpp_shaded_1),[1:1:CanopyRTMod.canopy.nlayers],lw=3, label=\"Vcmax25=90 - shaded\")\n",
    "plot!(reverse(gpp_shaded_2),[1:1:CanopyRTMod.canopy.nlayers],lw=3, label=\"Vcmax25=50 - shaded\")\n",
    "plot!(reverse(gpp_total_1),[1:1:CanopyRTMod.canopy.nlayers],lw=3, label=\"Vcmax25=90 - total\")\n",
    "plot!(reverse(gpp_total_2),[1:1:CanopyRTMod.canopy.nlayers],lw=3, label=\"Vcmax25=50 - total\",legend=:bottomright)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Get some PAR response curves"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Vcmax25=90Total GPP =3.0430434\n",
      "Vcmax25=50Total GPP =2.3896337"
     ]
    }
   ],
   "source": [
    "print(\"Vcmax25=90\",\"Total GPP =\",sum(gpp_total_1)./CanopyRTMod.canopy.nlayers,\"\\n\")\n",
    "print(\"Vcmax25=50\",\"Total GPP =\",sum(gpp_total_2)./CanopyRTMod.canopy.nlayers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Test T dependence\n",
    "T_ = Float32[]\n",
    "ag_T_  = Float32[]\n",
    "an_T_  = Float32[]\n",
    "vcmax_T_  = Float32[]\n",
    "electron_co2_T_  = Float32[]\n",
    "gamma_T_  = Float32[]\n",
    "#f.APAR = 500\n",
    "f.APAR = APAR_sunlit + APAR_shaded\n",
    "\n",
    "for T in 260:1:320\n",
    "    Leaf.LeafPhotosynthesis(f,l,T,f.APAR);\n",
    "    push!(T_, T)\n",
    "    push!(ag_T_, f.ag)\n",
    "    push!(an_T_, f.an)\n",
    "    push!(vcmax_T_, l.vcmax)\n",
    "    push!(electron_co2_T_, l.CO2_per_electron)\n",
    "    push!(gamma_T_ , l.Γstar)\n",
    "end"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
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Q2151.46 427.25 2150.65 429.171 Q2149.86 431.069 2147.76 433.662 Q2147.18 434.333 2144.08 437.551 Q2140.97 440.745 2135.33 446.509 Z\" fill=\"#000000\" fill-rule=\"evenodd\" fill-opacity=\"1\" /><path clip-path=\"url(#clip9200)\" d=\"M 0 0 M2169.56 419.958 L2157.76 438.407 L2169.56 438.407 L2169.56 419.958 M2168.33 415.884 L2174.21 415.884 L2174.21 438.407 L2179.15 438.407 L2179.15 442.296 L2174.21 442.296 L2174.21 450.444 L2169.56 450.444 L2169.56 442.296 L2153.96 442.296 L2153.96 437.782 L2168.33 415.884 Z\" fill=\"#000000\" fill-rule=\"evenodd\" fill-opacity=\"1\" /><path clip-path=\"url(#clip9200)\" d=\"M 0 0 M2197.06 419.958 L2185.26 438.407 L2197.06 438.407 L2197.06 419.958 M2195.83 415.884 L2201.71 415.884 L2201.71 438.407 L2206.64 438.407 L2206.64 442.296 L2201.71 442.296 L2201.71 450.444 L2197.06 450.444 L2197.06 442.296 L2181.46 442.296 L2181.46 437.782 L2195.83 415.884 Z\" fill=\"#000000\" fill-rule=\"evenodd\" fill-opacity=\"1\" /><path clip-path=\"url(#clip9200)\" d=\"M 0 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      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m = f.APAR\n",
    "plot(T_.-273.15, ag_T_, lw=3, label=\"Ag; Vcmax25=90, PAR=$m\",  xlabel=\"T (degC)\")\n",
    "plot!(T_.-273.15, an_T_, lw=3, label=\"An; Vcmax25=90, PAR=$m\")\n",
    "plot!(T_.-273.15, vcmax_T_/10, lw=3, label=\"Vcmax/10; Vcmax25=90, PAR=$m\")\n",
    "plot!(T_.-273.15, electron_co2_T_*100, lw=3, label=\"CO2 per electron*100; Vcmax25=90, PAR=$m\")\n",
    "plot!(T_.-273.15, gamma_T_/10, lw=3, label=\"CO2 Compensation Point/10; Vcmax25=90, PAR=$m\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Simulating photosynthesis in SSA-OA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "┌ Info: Precompiling DataFrames [a93c6f00-e57d-5684-b7b6-d8193f3e46c0]\n",
      "└ @ Base loading.jl:1273\n",
      "┌ Info: Precompiling CSV [336ed68f-0bac-5ca0-87d4-7b16caf5d00b]\n",
      "└ @ Base loading.jl:1273\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "thread = 1 warning: only found 10 / 11 columns on data row: 637. Filling remaining columns with `missing`\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table class=\"data-frame\"><thead><tr><th></th><th>DATE</th><th>Tair</th><th>VPD</th><th>PAR</th><th>SW</th><th>Press</th><th>DIF</th><th>NEE</th><th>RECO</th></tr><tr><th></th><th>String</th><th>Float64</th><th>Float64</th><th>Float64</th><th>Float64</th><th>Float64</th><th>Float64</th><th>Float64</th><th>Float64</th></tr></thead><tbody><p>637 rows × 11 columns (omitted printing of 2 columns)</p><tr><th>1</th><td>7/11/96 1:00</td><td>14.9</td><td>1.79</td><td>27.62</td><td>60.94</td><td>936.99</td><td>0.05</td><td>-0.85</td><td>6.64</td></tr><tr><th>2</th><td>7/11/96 1:30</td><td>14.87</td><td>1.26</td><td>17.93</td><td>39.64</td><td>936.83</td><td>0.04</td><td>-1.21</td><td>6.6</td></tr><tr><th>3</th><td>7/11/96 2:00</td><td>15.02</td><td>0.79</td><td>20.37</td><td>46.11</td><td>936.8</td><td>0.09</td><td>-3.03</td><td>6.54</td></tr><tr><th>4</th><td>7/11/96 2:30</td><td>15.1</td><td>1.1</td><td>12.7</td><td>29.38</td><td>936.71</td><td>0.1</td><td>-3.41</td><td>6.51</td></tr><tr><th>5</th><td>7/11/96 3:00</td><td>14.98</td><td>1.44</td><td>6.92</td><td>16.41</td><td>936.83</td><td>0.29</td><td>-2.19</td><td>6.51</td></tr><tr><th>6</th><td>7/11/96 3:30</td><td>14.92</td><td>0.58</td><td>1.27</td><td>3.02</td><td>936.97</td><td>0.14</td><td>-5.21</td><td>6.48</td></tr><tr><th>7</th><td>7/11/96 4:00</td><td>14.87</td><td>0.43</td><td>0.23</td><td>0.38</td><td>937.14</td><td>0.06</td><td>-5.41</td><td>5.41</td></tr><tr><th>8</th><td>7/11/96 4:30</td><td>14.89</td><td>0.49</td><td>0.02</td><td>0.07</td><td>937.28</td><td>0.06</td><td>-5.61</td><td>5.61</td></tr><tr><th>9</th><td>7/11/96 5:00</td><td>14.94</td><td>1.25</td><td>0.0</td><td>0.12</td><td>937.55</td><td>0.06</td><td>-5.81</td><td>5.81</td></tr><tr><th>10</th><td>7/11/96 5:30</td><td>14.9</td><td>2.48</td><td>0.0</td><td>0.24</td><td>937.73</td><td>0.06</td><td>-6.01</td><td>6.01</td></tr><tr><th>11</th><td>7/11/96 6:00</td><td>14.76</td><td>3.06</td><td>0.0</td><td>0.0</td><td>937.93</td><td>1.0</td><td>-6.21</td><td>6.21</td></tr><tr><th>12</th><td>7/11/96 6:30</td><td>14.57</td><td>5.03</td><td>0.0</td><td>0.0</td><td>938.14</td><td>1.0</td><td>-5.71</td><td>5.71</td></tr><tr><th>13</th><td>7/11/96 7:00</td><td>14.41</td><td>5.37</td><td>0.0</td><td>0.0</td><td>938.43</td><td>1.0</td><td>-5.21</td><td>5.21</td></tr><tr><th>14</th><td>7/11/96 7:30</td><td>14.43</td><td>6.66</td><td>0.0</td><td>0.08</td><td>938.44</td><td>0.06</td><td>-5.28</td><td>5.28</td></tr><tr><th>15</th><td>7/11/96 8:00</td><td>14.25</td><td>4.57</td><td>0.0</td><td>0.1</td><td>938.6</td><td>0.06</td><td>-5.35</td><td>5.35</td></tr><tr><th>16</th><td>7/11/96 8:30</td><td>14.4</td><td>5.8</td><td>0.0</td><td>0.07</td><td>938.79</td><td>0.06</td><td>-5.42</td><td>5.42</td></tr><tr><th>17</th><td>7/11/96 9:00</td><td>14.46</td><td>7.79</td><td>0.0</td><td>0.0</td><td>939.0</td><td>1.0</td><td>-6.1</td><td>6.1</td></tr><tr><th>18</th><td>7/11/96 9:30</td><td>14.59</td><td>11.9</td><td>0.0</td><td>0.12</td><td>939.33</td><td>0.06</td><td>-6.78</td><td>6.78</td></tr><tr><th>19</th><td>7/11/96 10:00</td><td>14.44</td><td>12.76</td><td>0.0</td><td>0.0</td><td>939.48</td><td>1.0</td><td>-4.13</td><td>4.13</td></tr><tr><th>20</th><td>7/11/96 10:30</td><td>14.23</td><td>11.38</td><td>0.08</td><td>0.17</td><td>939.77</td><td>0.06</td><td>-5.0</td><td>5.0</td></tr><tr><th>21</th><td>7/11/96 11:00</td><td>14.49</td><td>13.63</td><td>1.69</td><td>8.51</td><td>940.08</td><td>0.37</td><td>-2.17</td><td>5.95</td></tr><tr><th>22</th><td>7/11/96 11:30</td><td>14.84</td><td>16.77</td><td>10.6</td><td>36.94</td><td>940.4</td><td>0.87</td><td>-1.21</td><td>5.93</td></tr><tr><th>23</th><td>7/11/96 12:00</td><td>15.13</td><td>18.37</td><td>21.37</td><td>58.59</td><td>940.64</td><td>0.46</td><td>1.53</td><td>5.93</td></tr><tr><th>24</th><td>7/11/96 12:30</td><td>15.14</td><td>17.92</td><td>39.79</td><td>89.47</td><td>940.94</td><td>0.37</td><td>4.53</td><td>5.94</td></tr><tr><th>25</th><td>7/11/96 13:00</td><td>15.26</td><td>18.38</td><td>50.4</td><td>112.26</td><td>941.5</td><td>0.28</td><td>4.73</td><td>5.94</td></tr><tr><th>26</th><td>7/11/96 13:30</td><td>15.43</td><td>18.85</td><td>69.19</td><td>156.59</td><td>941.89</td><td>0.32</td><td>7.27</td><td>5.96</td></tr><tr><th>27</th><td>7/11/96 14:00</td><td>16.22</td><td>24.61</td><td>135.63</td><td>314.58</td><td>942.42</td><td>0.73</td><td>13.53</td><td>5.99</td></tr><tr><th>28</th><td>7/11/96 14:30</td><td>17.38</td><td>33.9</td><td>188.22</td><td>433.61</td><td>942.86</td><td>0.83</td><td>15.56</td><td>6.08</td></tr><tr><th>29</th><td>7/11/96 15:00</td><td>18.53</td><td>43.33</td><td>222.69</td><td>509.55</td><td>943.19</td><td>0.84</td><td>19.64</td><td>6.24</td></tr><tr><th>30</th><td>7/11/96 15:30</td><td>19.8</td><td>58.82</td><td>244.41</td><td>556.27</td><td>943.53</td><td>0.83</td><td>15.7</td><td>6.42</td></tr><tr><th>&vellip;</th><td>&vellip;</td><td>&vellip;</td><td>&vellip;</td><td>&vellip;</td><td>&vellip;</td><td>&vellip;</td><td>&vellip;</td><td>&vellip;</td><td>&vellip;</td></tr></tbody></table>"
      ],
      "text/latex": [
       "\\begin{tabular}{r|cccccccccc}\n",
       "\t& DATE & Tair & VPD & PAR & SW & Press & DIF & NEE & RECO & \\\\\n",
       "\t\\hline\n",
       "\t& String & Float64 & Float64 & Float64 & Float64 & Float64 & Float64 & Float64 & Float64 & \\\\\n",
       "\t\\hline\n",
       "\t1 & 7/11/96 1:00 & 14.9 & 1.79 & 27.62 & 60.94 & 936.99 & 0.05 & -0.85 & 6.64 & $\\dots$ \\\\\n",
       "\t2 & 7/11/96 1:30 & 14.87 & 1.26 & 17.93 & 39.64 & 936.83 & 0.04 & -1.21 & 6.6 & $\\dots$ \\\\\n",
       "\t3 & 7/11/96 2:00 & 15.02 & 0.79 & 20.37 & 46.11 & 936.8 & 0.09 & -3.03 & 6.54 & $\\dots$ \\\\\n",
       "\t4 & 7/11/96 2:30 & 15.1 & 1.1 & 12.7 & 29.38 & 936.71 & 0.1 & -3.41 & 6.51 & $\\dots$ \\\\\n",
       "\t5 & 7/11/96 3:00 & 14.98 & 1.44 & 6.92 & 16.41 & 936.83 & 0.29 & -2.19 & 6.51 & $\\dots$ \\\\\n",
       "\t6 & 7/11/96 3:30 & 14.92 & 0.58 & 1.27 & 3.02 & 936.97 & 0.14 & -5.21 & 6.48 & $\\dots$ \\\\\n",
       "\t7 & 7/11/96 4:00 & 14.87 & 0.43 & 0.23 & 0.38 & 937.14 & 0.06 & -5.41 & 5.41 & $\\dots$ \\\\\n",
       "\t8 & 7/11/96 4:30 & 14.89 & 0.49 & 0.02 & 0.07 & 937.28 & 0.06 & -5.61 & 5.61 & $\\dots$ \\\\\n",
       "\t9 & 7/11/96 5:00 & 14.94 & 1.25 & 0.0 & 0.12 & 937.55 & 0.06 & -5.81 & 5.81 & $\\dots$ \\\\\n",
       "\t10 & 7/11/96 5:30 & 14.9 & 2.48 & 0.0 & 0.24 & 937.73 & 0.06 & -6.01 & 6.01 & $\\dots$ \\\\\n",
       "\t11 & 7/11/96 6:00 & 14.76 & 3.06 & 0.0 & 0.0 & 937.93 & 1.0 & -6.21 & 6.21 & $\\dots$ \\\\\n",
       "\t12 & 7/11/96 6:30 & 14.57 & 5.03 & 0.0 & 0.0 & 938.14 & 1.0 & -5.71 & 5.71 & $\\dots$ \\\\\n",
       "\t13 & 7/11/96 7:00 & 14.41 & 5.37 & 0.0 & 0.0 & 938.43 & 1.0 & -5.21 & 5.21 & $\\dots$ \\\\\n",
       "\t14 & 7/11/96 7:30 & 14.43 & 6.66 & 0.0 & 0.08 & 938.44 & 0.06 & -5.28 & 5.28 & $\\dots$ \\\\\n",
       "\t15 & 7/11/96 8:00 & 14.25 & 4.57 & 0.0 & 0.1 & 938.6 & 0.06 & -5.35 & 5.35 & $\\dots$ \\\\\n",
       "\t16 & 7/11/96 8:30 & 14.4 & 5.8 & 0.0 & 0.07 & 938.79 & 0.06 & -5.42 & 5.42 & $\\dots$ \\\\\n",
       "\t17 & 7/11/96 9:00 & 14.46 & 7.79 & 0.0 & 0.0 & 939.0 & 1.0 & -6.1 & 6.1 & $\\dots$ \\\\\n",
       "\t18 & 7/11/96 9:30 & 14.59 & 11.9 & 0.0 & 0.12 & 939.33 & 0.06 & -6.78 & 6.78 & $\\dots$ \\\\\n",
       "\t19 & 7/11/96 10:00 & 14.44 & 12.76 & 0.0 & 0.0 & 939.48 & 1.0 & -4.13 & 4.13 & $\\dots$ \\\\\n",
       "\t20 & 7/11/96 10:30 & 14.23 & 11.38 & 0.08 & 0.17 & 939.77 & 0.06 & -5.0 & 5.0 & $\\dots$ \\\\\n",
       "\t21 & 7/11/96 11:00 & 14.49 & 13.63 & 1.69 & 8.51 & 940.08 & 0.37 & -2.17 & 5.95 & $\\dots$ \\\\\n",
       "\t22 & 7/11/96 11:30 & 14.84 & 16.77 & 10.6 & 36.94 & 940.4 & 0.87 & -1.21 & 5.93 & $\\dots$ \\\\\n",
       "\t23 & 7/11/96 12:00 & 15.13 & 18.37 & 21.37 & 58.59 & 940.64 & 0.46 & 1.53 & 5.93 & $\\dots$ \\\\\n",
       "\t24 & 7/11/96 12:30 & 15.14 & 17.92 & 39.79 & 89.47 & 940.94 & 0.37 & 4.53 & 5.94 & $\\dots$ \\\\\n",
       "\t25 & 7/11/96 13:00 & 15.26 & 18.38 & 50.4 & 112.26 & 941.5 & 0.28 & 4.73 & 5.94 & $\\dots$ \\\\\n",
       "\t26 & 7/11/96 13:30 & 15.43 & 18.85 & 69.19 & 156.59 & 941.89 & 0.32 & 7.27 & 5.96 & $\\dots$ \\\\\n",
       "\t27 & 7/11/96 14:00 & 16.22 & 24.61 & 135.63 & 314.58 & 942.42 & 0.73 & 13.53 & 5.99 & $\\dots$ \\\\\n",
       "\t28 & 7/11/96 14:30 & 17.38 & 33.9 & 188.22 & 433.61 & 942.86 & 0.83 & 15.56 & 6.08 & $\\dots$ \\\\\n",
       "\t29 & 7/11/96 15:00 & 18.53 & 43.33 & 222.69 & 509.55 & 943.19 & 0.84 & 19.64 & 6.24 & $\\dots$ \\\\\n",
       "\t30 & 7/11/96 15:30 & 19.8 & 58.82 & 244.41 & 556.27 & 943.53 & 0.83 & 15.7 & 6.42 & $\\dots$ \\\\\n",
       "\t$\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ & $\\dots$ &  \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "637×11 DataFrame. Omitted printing of 5 columns\n",
       "│ Row │ DATE         │ Tair    │ VPD     │ PAR     │ SW      │ Press   │\n",
       "│     │ \u001b[90mString\u001b[39m       │ \u001b[90mFloat64\u001b[39m │ \u001b[90mFloat64\u001b[39m │ \u001b[90mFloat64\u001b[39m │ \u001b[90mFloat64\u001b[39m │ \u001b[90mFloat64\u001b[39m │\n",
       "├─────┼──────────────┼─────────┼─────────┼─────────┼─────────┼─────────┤\n",
       "│ 1   │ 7/11/96 1:00 │ 14.9    │ 1.79    │ 27.62   │ 60.94   │ 936.99  │\n",
       "│ 2   │ 7/11/96 1:30 │ 14.87   │ 1.26    │ 17.93   │ 39.64   │ 936.83  │\n",
       "│ 3   │ 7/11/96 2:00 │ 15.02   │ 0.79    │ 20.37   │ 46.11   │ 936.8   │\n",
       "│ 4   │ 7/11/96 2:30 │ 15.1    │ 1.1     │ 12.7    │ 29.38   │ 936.71  │\n",
       "│ 5   │ 7/11/96 3:00 │ 14.98   │ 1.44    │ 6.92    │ 16.41   │ 936.83  │\n",
       "│ 6   │ 7/11/96 3:30 │ 14.92   │ 0.58    │ 1.27    │ 3.02    │ 936.97  │\n",
       "│ 7   │ 7/11/96 4:00 │ 14.87   │ 0.43    │ 0.23    │ 0.38    │ 937.14  │\n",
       "│ 8   │ 7/11/96 4:30 │ 14.89   │ 0.49    │ 0.02    │ 0.07    │ 937.28  │\n",
       "│ 9   │ 7/11/96 5:00 │ 14.94   │ 1.25    │ 0.0     │ 0.12    │ 937.55  │\n",
       "│ 10  │ 7/11/96 5:30 │ 14.9    │ 2.48    │ 0.0     │ 0.24    │ 937.73  │\n",
       "⋮\n",
       "│ 627 │ 7/24/96 2:00 │ 18.78   │ 65.86   │ 38.1    │ 85.59   │ 951.18  │\n",
       "│ 628 │ 7/24/96 2:30 │ 18.33   │ 57.06   │ 34.44   │ 58.93   │ 951.3   │\n",
       "│ 629 │ 7/24/96 3:00 │ 17.7    │ 52.47   │ 11.57   │ 27.64   │ 951.51  │\n",
       "│ 630 │ 7/24/96 3:30 │ 16.61   │ 41.64   │ 2.37    │ 5.22    │ 951.67  │\n",
       "│ 631 │ 7/24/96 4:00 │ 15.64   │ 28.82   │ 0.1     │ 0.58    │ 951.73  │\n",
       "│ 632 │ 7/24/96 4:30 │ 15.81   │ 29.99   │ 0.01    │ 0.47    │ 951.91  │\n",
       "│ 633 │ 7/24/96 5:00 │ 15.62   │ 29.63   │ 0.0     │ 0.36    │ 951.94  │\n",
       "│ 634 │ 7/24/96 5:30 │ 15.26   │ 28.19   │ 0.0     │ 0.35    │ 951.87  │\n",
       "│ 635 │ 7/24/96 6:00 │ 15.37   │ 30.35   │ 0.0     │ 0.0     │ 952.0   │\n",
       "│ 636 │ 7/24/96 6:30 │ 15.45   │ 34.97   │ 0.0     │ 0.0     │ 952.03  │\n",
       "│ 637 │ 7/24/96 7:00 │ 15.4    │ 36.52   │ 0.0     │ 0.12    │ 951.96  │"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "using DataFrames, CSV\n",
    "\n",
    "#CSV.read(\"/Users/braghier/Desktop/SSA_OA_input.csv\"; header=true)\n",
    "\n",
    "f1 = CSV.read(\"/Users/braghier/Desktop/SSA_OA_input.csv\"; header=true)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "114-element Array{Float32,1}:\n",
       " 423.91205 \n",
       " 456.2974  \n",
       " 464.9233  \n",
       " 470.93362 \n",
       " 566.8391  \n",
       " 619.44336 \n",
       " 641.89233 \n",
       " 658.91205 \n",
       " 648.7285  \n",
       " 677.19165 \n",
       " 667.3115  \n",
       " 653.706   \n",
       " 675.8207  \n",
       "   ⋮       \n",
       "  58.318916\n",
       "  59.031662\n",
       "  58.342964\n",
       "  52.554035\n",
       "  49.43001 \n",
       "  50.346333\n",
       "  48.508892\n",
       "  44.747684\n",
       "  41.09356 \n",
       "  38.33341 \n",
       "  33.06685 \n",
       "  28.3946  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "arrayOfLeaves = Array{leafbio{FT,length(wl), length(wle), length(wlf),length(wle)*length(wlf)}, 1}(undef, CanopyRTMod.canopy.nlayers)\n",
    "for i = 1:CanopyRTMod.canopy.nlayers\n",
    "    #@show i\n",
    "    arrayOfLeaves[i] = leafbio{FT, length(wl), length(wle), length(wlf),length(wle)*length(wlf)}()\n",
    "    CanopyRTMod.fluspect!(arrayOfLeaves[i], CanopyRTMod.optis)\n",
    "end\n",
    "\n",
    "SW_dif = sunRad.E_diffuse[:]\n",
    "SW_dir = sunRad.E_direct[:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.0\t1.001641\n",
      "0.0\t1.0017166\n",
      "0.0\t1.0017068\n",
      "0.0\t1.0017922\n",
      "0.0\t1.0017211\n",
      "0.0\t1.0016924\n",
      "0.0\t1.0016311\n",
      "0.0\t1.001703\n",
      "0.0\t1.0018022\n",
      "3.79\t1.6540382\n",
      "4.72\t3.9707024\n",
      "7.46\t6.4829164\n",
      "10.47\t9.046558\n",
      "10.67\t11.693302\n",
      "13.23\t14.397043\n",
      "19.52\t17.455538\n",
      "21.64\t20.756193\n",
      "25.88\t24.043058\n",
      "22.11\t27.219091\n",
      "27.43\t29.788355\n",
      "23.19\t32.122856\n",
      "30.13\t34.270744\n",
      "26.14\t35.780796\n",
      "18.82\t36.808857\n",
      "23.83\t37.485077\n",
      "22.49\t37.78602\n",
      "31.0\t37.548985\n",
      "25.58\t36.890694\n",
      "23.27\t35.92003\n",
      "17.71\t34.57487\n",
      "13.34\t32.94067\n",
      "11.9\t31.005924\n",
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      "17.32\t25.937567\n",
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      "10.41\t20.161352\n",
      "10.53\t17.023382\n",
      "11.64\t13.932643\n",
      "9.19\t10.930367\n",
      "2.56\t7.9584537\n",
      "0.82\t5.1167192\n",
      "2.95\t2.4741387\n",
      "2.18\t1.0002048\n",
      "0.0\t1.0003382\n",
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      "0.0\t1.0006438\n",
      "0.0\t1.0007449\n",
      "0.0\t1.0008407\n",
      "0.0\t1.000961\n",
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      "0.0\t1.0014102\n",
      "0.0\t1.0016842\n",
      "0.0\t1.0017067\n",
      "0.0\t1.0017546\n",
      "0.0\t1.0018373\n",
      "0.0\t1.0016599\n",
      "0.0\t1.0017787\n",
      "-2.91\t1.3005608\n",
      "-5.51\t2.4645984\n",
      "5.12\t4.190609\n",
      "4.48\t5.997138\n",
      "8.62\t7.557066\n",
      "12.84\t9.672384\n",
      "12.12\t13.189751\n",
      "18.74\t17.611923\n",
      "25.79\t20.907598\n",
      "25.92\t24.212097\n",
      "31.91\t28.237652\n",
      "36.14\t30.600622\n",
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      "30.16\t34.144978\n",
      "35.9\t35.611423\n",
      "29.95\t37.045567\n",
      "24.71\t37.51335\n",
      "32.63\t37.537952\n",
      "28.56\t37.05239\n",
      "35.27\t36.126625\n",
      "20.85\t34.773598\n",
      "29.0\t33.02831\n",
      "24.49\t31.004045\n",
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      "14.31\t22.970469\n",
      "20.94\t20.241978\n",
      "13.44\t17.101145\n",
      "1.21\t13.825623\n",
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      "0.0\t1.0009509\n",
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      "0.0\t1.0014731\n",
      "0.0\t1.0011351\n",
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      "0.0\t1.0013713\n",
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      "7.0\t2.2941604\n",
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      "0.0\t1.000966\n",
      "0.0\t1.001337\n",
      "0.0\t1.0016233\n",
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      "0.0\t1.0012289\n",
      "0.0\t1.0014638\n",
      "0.0\t1.0019506\n",
      "0.0\t1.0025281\n",
      "0.0\t1.0016712\n",
      "0.0\t1.0018142\n",
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   "source": [
    "\n",
    "GPP_1 = []\n",
    "GPP_2 = []\n",
    "GPP_obs = []\n",
    "\n",
    "\n",
    "#for i=12:1:72\n",
    "for i=12:1:72+90\n",
    "\n",
    "if rad2deg(acos(f1.COSSZA[i])) < 90.\n",
    "   CanopyRTMod.angles.tts = rad2deg(acos(f1.COSSZA[i]));\n",
    "else\n",
    "   CanopyRTMod.angles.tts = 89.9;\n",
    "end \n",
    "    \n",
    "CanopyRTMod.soil.albedo_SW[:] .=0.11;\n",
    "CanopyRTMod.canopy.LAI = 4.6\n",
    "CanopyRTMod.canopy.Ω = 1.0\n",
    "\n",
    "\n",
    "\n",
    "#sunRad.E_diffuse[28] = f1.PAR[i].*f1.DIF[i].*100.\n",
    "#sunRad.E_direct[28] = f1.PAR[i].*100.\n",
    "    \n",
    "frac = f1.SW[i]./(mean(SW_dir) .+ mean(SW_dif))\n",
    "sunRad.E_diffuse = SW_dif.*frac\n",
    "sunRad.E_direct = SW_dir.*frac \n",
    "\n",
    "    \n",
    "CanopyRTMod.fluspect!(leaf, CanopyRTMod.optis)\n",
    "CanopyRTMod.computeCanopyGeomProps!(canopy, angles,canOpt)\n",
    "CanopyRTMod.computeCanopyMatrices!(arrayOfLeaves,canOpt);\n",
    "\n",
    "# Create a leaf structure\n",
    "\n",
    "l = leaf_params{Float32}();\n",
    "l2 = leaf_params{Float32}();\n",
    "\n",
    "# Create a Flux structure\n",
    "\n",
    "f = Leaf.fluxes{Float32}();\n",
    "\n",
    "# initialize some reasonable values\n",
    "\n",
    "f.je = 100;\n",
    "f.gbc = 100;\n",
    "f.gbv = 100;\n",
    "f.ceair = f1.VPD[i].*100.;\n",
    "f.eair = f1.VPD[i].*100.;\n",
    "\n",
    "\n",
    "#vertical mean of net PAR absorbed by Cab of sunlit leaves\"\n",
    "\n",
    "APAR_sunlit = mean(CanopyRTMod.canOpt.Ps[1:end-1].*mean(CanopyRTMod.canRad.absPAR_sun*1e6, dims=1:2)[1,1,:]);  \n",
    "\n",
    "#vertical mean of net PAR absorbed by Cab of shaded leaves\"\n",
    "\n",
    "APAR_shaded = mean((1 .- CanopyRTMod.canOpt.Ps[1:end-1]).*mean(CanopyRTMod.canRad.absPAR_shade*1e6, dims=1:2)[1,1,:]);  \n",
    "f.APAR = APAR_sunlit + APAR_shaded\n",
    "\n",
    "l.Kn = 2.44\n",
    "\n",
    "#Temperature em Celsius\n",
    "Temp = f1.Tair[i];\n",
    "\n",
    "apar = Float32[]\n",
    "gpp_sunlit_1  = Float32[]\n",
    "gpp_shaded_1  = Float32[]\n",
    "apar_ = Float32[]\n",
    "gpp_sunlit_2  = Float32[]\n",
    "gpp_shaded_2  = Float32[]\n",
    "gpp_total_1  = Float32[]\n",
    "gpp_total_2  = Float32[]\n",
    "f.cair = 380\n",
    "l.vcmax25 = 45\n",
    "l.jmax25 = 45*1.9\n",
    "l2.vcmax25 = 25\n",
    "l2.jmax25 = 25*1.9\n",
    "\n",
    "\n",
    "vertical_APAR_sunlit = CanopyRTMod.canOpt.Ps[1:end-1].*mean(CanopyRTMod.canRad.absPAR_sun*1e6, dims=1:2)[1,1,:]\n",
    "vertical_APAR_shaded =(1 .- CanopyRTMod.canOpt.Ps[1:end-1]).*mean(CanopyRTMod.canRad.absPAR_shade*1e6, dims=1:2)[1,1,:] \n",
    "vertical_APAR = vertical_APAR_sunlit .+ vertical_APAR_shaded\n",
    "\n",
    "#Sunlit\n",
    "for f.APAR in vertical_APAR_sunlit\n",
    "    Leaf.LeafPhotosynthesis(f,l,(Temp + 273.15),f.APAR);\n",
    "    push!(apar, f.APAR)\n",
    "    push!(gpp_sunlit_1, f.an)\n",
    "    Leaf.LeafPhotosynthesis(f,l2,(Temp + 273.15),f.APAR);\n",
    "    push!(apar_, f.APAR)\n",
    "    push!(gpp_sunlit_2, f.an)\n",
    "    #println(f.APAR, \" \", f.ag, \" \", f.an)\n",
    "end\n",
    "\n",
    "#Shaded\n",
    "for f.APAR in vertical_APAR_shaded\n",
    "    Leaf.LeafPhotosynthesis(f,l,(Temp + 273.15),f.APAR);\n",
    "    push!(apar, f.APAR)\n",
    "    push!(gpp_shaded_1, f.an)\n",
    "    Leaf.LeafPhotosynthesis(f,l2,(Temp + 273.15),f.APAR);\n",
    "    push!(apar_, f.APAR)\n",
    "    push!(gpp_shaded_2, f.an)\n",
    "end\n",
    "\n",
    "gpp_total_1 = ( CanopyRTMod.canOpt.Ps[1:end-1]).*(gpp_sunlit_1) + (1 .-CanopyRTMod.canOpt.Ps[1:end-1].*(gpp_shaded_1))./CanopyRTMod.canopy.nlayers\n",
    "gpp_total_2 = ( CanopyRTMod.canOpt.Ps[1:end-1]).*(gpp_sunlit_2) + (1 .-CanopyRTMod.canOpt.Ps[1:end-1].*(gpp_shaded_2))./CanopyRTMod.canopy.nlayers\n",
    "    \n",
    "push!(GPP_1, sum(gpp_total_1))\n",
    "push!(GPP_2, sum(gpp_total_2))\n",
    "push!(GPP_obs, f1.GPP[i])\n",
    "    \n",
    "print(f1.GPP[i],\"\\t\", sum(gpp_total_2),\"\\n\")\n",
    "end"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {},
   "outputs": [
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      ]
     },
     "execution_count": 130,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "i=12:1:72+90\n",
    "\n",
    "#plot(i, GPP_1,label=\"GPP_1\")\n",
    "plot(i, GPP_2,label=\"GPP_2\",title = \"SSA-OA \",lw = 3)\n",
    "plot!(i, GPP_obs,label=\"Obs\",lw = 2)\n",
    "\n",
    "\n",
    "ylabel!(\"GPP (umolm-2s-1)\")\n",
    "xlabel!(\"Time (30 min intervals since 7/11/1996 01:00 UTC)\")\n",
    "#plot!(xlims = (0.0, 90.), ylims = (-0.05, 1.0), xticks = 0:20:91., yticks = 0:0.2:1.0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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   "mimetype": "application/julia",
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